Gait Period Detection Based on Regional Characteristics Analysis

The problem of gait period detection was transformed to that of regional characteristics analysis in a single frame, namely, the gait period was divided according to region characteristic variable in each frame. A method for gait period detection based on regional characteristics analysis is proposed in this paper. Gait video sequences were coarsely classified into frontal and non-frontal ones in the first instance. Swinging arm regions was detected for frontal gaits, instead regional characteristics such as area, centroid, moment, special points and bounding box were detected for non-frontal gaits. Not only the computation is small, but also this proposed method has already achieved the precision of human subjective judgement. Especially, gait period detection based on ellipse fitting is robust to noise. Moreover, with the scaling invariance and shift invariance attributes, this method can be used before the standardized and centralized image processing. Therefore, the processing time of earlier work in gait recognition is reduced significantly.